Audio fingerprinting provides the ability to link short, unlabeled, snippets of audio content to corresponding data. It provides the ability to automatically identify and cross-link background audio, such as songs, and the tagging of songs with metadata (e.g., the performing artist's name, album name, etc.) can be accomplished. Unlike many competing technologies, a goal of audio fingerprinting is to perform the recognition without imposing extraneous hardware restraints to automatic detection and/or replacement, as well as without extraneous data transmission.
Various challenges are posed when systems do not function with exact bit-level matches when comparing content. The system may be functioning with only short snippets of audio content when a full song is not easily available. Because song fragments may be utilized, no fine or even coarse alignment of the audio content occurs, and the match comparison may occur anywhere within a song. Further, songs are commonly “sampled” into other songs, thereby making the identification of potential matches more ambiguous. When identifying songs played on a radio, for example, a radio station may change the speed of a song to fit their programming requirements. Additionally, there are difficulties introduced through the numerous forms of playback available to the end consumer. Music that is played through a cell phone, computer speakers, or high-end audio equipment will have very different audio characteristics.